Business data Mining Techniques

Medicare Fee-For Service Provider Utilization & Payment Data

Part D Prescriber Public Use File:

A Methodological Overview

April 7, 2015

Prepared by: The Centers for Medicare and Medicaid Services,

Office of Enterprise Data and Analytics

Table of Contents

Table of Contents .......................................................................................................................................... 2

1. Background ............................................................................................................................................... 3

2. Key data sources ....................................................................................................................................... 3

3. Population ................................................................................................................................................. 3

4. Aggregation ............................................................................................................................................... 4

5. Data Contents ........................................................................................................................................... 5

6. Data Limitations: ..................................................................................................................................... 10

APPENDIX A – File Attributes ...................................................................................................................... 12

Table 1. NPI / Drug Name / Generic Name Detail File Layout ................................................................ 12

Table 2. NPI Summary File Layout .......................................................................................................... 13

Table 3. National and State, Drug Name / Generic Name Summary File Layout ................................... 14

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1. Background

As part of the Obama Administration’s efforts to make our healthcare system more transparent, affordable, and accountable, the Centers for Medicare & Medicaid Services (CMS) has prepared a public data set, the Part D Prescriber Public Use File (herein referred to as the “Part D Prescriber PUF”), with information on prescription drug events (PDEs) incurred by Medicare beneficiaries with a Part D prescription drug plan. The Part D Prescriber PUF is organized by National Provider Identifier (NPI) and drug name and contains information on drug utilization (claim counts and day supply) and total drug costs.

2. Key data sources

The primary data source for these data is the CMS 2013 Medicare Part D PDE Standard Analytic File (SAF) which include PDEs received through the submission cut-off date of 6/30/2014. The PDE SAF contains 100 percent of Medicare Part D final-action (i.e., all claim adjustments have been resolved) PDEs for beneficiaries who are enrolled in the Part D program. Beneficiary counts, claim counts, and total drug costs were summarized from this SAF. PDEs for over-the-counter drugs (indicated by drug coverage status code =”O”), which may be found in the PDE data due to their inclusion in an approved step-therapy protocols, were excluded from all summarizations. Drug brand names and generic names used in the summarization were appended to PDE records from First Databank’s MedKnowledgeTM drug information database by linking via National Drug Codes (NDCs).

Prescriber demographics are also incorporated in the Part D Prescriber PUF including name, credentials, gender, complete address and entity type from the National Plan & Provider Enumeration System (NPPES), which CMS developed to assign unique identifiers, known as National Provider Identifiers (NPIs), to health care providers. These demographics are self-reported by health care providers via NPPES at time of enrollment and updated periodically by CMS approved Electronic File Interchange Organizations (EFIO) that submit information on behalf of the provider. The provider must approve of the updates to NPPES. The demographics information provided in the Part D Prescriber PUF was extracted from NPPES at the end of calendar year 2014. Each prescriber’s most recent record was used for the prescriber’s data. For additional information on NPPES, please visit https://nppes.cms.hhs.gov/NPPES/Welcome.do.

3. Population

Information in the Part D Prescriber PUF is based on data from 35.7 million beneficiaries enrolled in the Medicare Part D prescription drug program, who comprise 68 percent of all Medicare beneficiaries. Approximately 23 million of these Part D beneficiaries are enrolled in stand-alone Prescription Drug Plans (PDP) and 13 million enrolled in Medicare Advantage Prescription Drug (MAPD) plans.

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The Part D Prescriber PUF includes data for prescribers who had a valid NPI and were included on Medicare Part D PDEs submitted by the Part D plan sponsors during the 2013 calendar year. The dataset contains information predominantly from individual providers, but also includes a small proportion of organizational providers, such as nursing homes, group practices, non-physician practitioners, residential treatment facilities, and ambulatory surgery centers and other providers.

4. Aggregation

The spending and utilization data in the Part D Prescriber PUF is aggregated to the following:

a) the NPI of the prescriber, and b) the drug name (brand name in the case of brand drugs) and generic name.

Each record in the dataset represents a distinct combination of NPI, drug (brand) name, and generic name. There can be multiple records for a given NPI based on the number of distinct drugs that were filled. For each prescriber and drug, the dataset includes the total number of prescriptions that were dispensed, (including original prescriptions and any refills), total days supply for these prescriptions, and the total drug cost. The total drug cost includes the ingredient cost of the medication, dispensing fees, sales tax, and any applicable administration fees. The total drug cost is based on the amounts paid by the Part D plan, Medicare beneficiary, government subsidies, and any other third-party payors. Data are provided on each record for all Medicare Part D beneficiaries and also separately limited to beneficiaries aged 65 years and older. In a very small number of cases, the drug name and generic name could not be determined from the NDC on the PDE record, and in these instances the drug name and generic name field on the file contains a null value.

In addition to the NPI/drug detail file, two types of summary files are also provided. One summary file is provided at the prescriber-level (i.e., one summary record per NPI). Note that this NPI summary has enhanced prescriber demographic information (e.g., full provider address) beyond what is provided in the NPI/drug detail file. Additionally, two summary files are provided at the drug name and generic name level, one at the national level and one at the state level. These summary files are individually summarized from the source PDE SAF data, and therefore do not represent a re-summarization of the Part D Prescriber PUF data.

To protect the privacy of Medicare beneficiaries, any aggregated records which are derived from 10 or fewer claims are excluded from the Part D Prescriber PUF. After these privacy redactions, the dataset retained information from 86.8% of claims and 78.1% of total costs. However, the higher-level summary files included in the release contain nearly complete information; the prescriber-level summary contains information on 99.91% of total claims and the national and state drug-level summaries contain information on 99.99 percent of claims.

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5. Data Contents

npi – National Provider Identifier (NPI) for the performing provider on the claim.

nppes_provider_last_org_name – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s last name. When the provider is registered as an organization (entity type code = ‘O’), this is the organization name.

nppes_provider_first_name – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s first name. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

nppes_provider_mi – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s middle initial. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

nppes_credentials – When the provider is registered in NPPES as an individual (entity type code=’I’), these are the provider’s credentials. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

nppes_provider_gender – When the provider is registered in NPPES as an individual (entity type code=’I’), this is the provider’s gender. When the provider is registered as an organization (entity type code = ‘O’), this will be blank.

nppes_entity_code – Type of entity reported in NPPES. An entity code of ‘I’ identifies providers registered as individuals and an entity type code of ‘O’ identifies providers registered as organizations.

nppes_provider_street1 – The first line of the provider’s street address, as reported in NPPES.

nppes_provider_street2 – The second line of the provider’s street address, as reported in NPPES.

nppes_provider_city – The city where the provider is located, as reported in NPPES.

nppes_provider_zip – The provider’s zip code, as reported in NPPES.

nppes_provider_state – The state where the provider is located, as reported in NPPES. The fifty U.S. states and the District of Columbia are reported by the state postal abbreviation. The following values are used for other areas:

'XX' = 'Unknown' 'AA' = 'Armed Forces Central/South America' 'AE' = 'Armed Forces Europe' 'AP' = 'Armed Forces Pacific' 'AS' = 'American Samoa' 'GU' = 'Guam' 'MP' = 'North Mariana Islands' 'PR' = 'Puerto Rico'

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'VI' = 'Virgin Islands' 'ZZ' = 'Foreign Country'

nppes_provider_country – The country where the provider is located, as reported in NPPES. The country code will be ‘US’ for any state or U.S possession. For foreign countries (i.e., state values of ‘ZZ’), the provider country values may include the following:

‘AE’ = ‘United Arab Emirates’ ‘IS’= ‘Iceland’ ‘AI’ = ‘Anguilla’ ‘IT’= ‘Italy’ ‘AR’= ‘Argentina’ ‘JO’ = ‘Jordan’ ‘AU’= ‘Australia’ ‘JP’= ‘Japan’ ‘BH’ = ‘Bahrain’ ‘KR’= ‘Korea’ ‘BM’ = ‘Bermuda’ ‘KW’ = ‘Kuwait’ ‘BR’= ‘Brazil’ ‘KY’ = ‘Cayman Islands’ ‘CA’= ‘Canada’ ‘LY’ = ‘Libya’ ‘CH’= ‘Switzerland’ ‘MG’ = ‘Madagascar’ ‘CN’= ‘China’ ‘MX’ = ‘Mexico’ ‘CO’= ‘Colombia’ ‘NL’= ‘Netherlands’ ‘DE’= ‘Germany’ ‘NO’ = ‘Norway’ ‘EC’ = ‘Ecuador’ ‘NZ’ = ‘New Zealand’ ‘EG’ = ‘Egypt’ ‘OM’ = ‘Oman’ ‘ES’= ‘Spain’ ‘PA’ = ‘Panama’ ‘FR’= ‘France’ ‘PK’= ‘Pakistan’ ‘GB’= ‘Great Britain’ ‘SA’= ‘Saudi Arabia’ ‘GR’ = ‘Greece’ ‘SE’= ‘Sweden’ ‘HU’= ‘Hungary’ ‘TH’ = ‘Thailand’ ‘IE’ = ‘Ireland’ ‘TR’= ‘Turkey’ ‘IL’= ‘Israel’ ‘UG’ = ‘Uganda’ ‘IN’= ‘India’ ‘VE’= ‘Venezuela’ ‘IQ’ = ‘Iraq’ ‘ZA’ = ‘South Africa’

specialty_description – Derived from the Medicare provider/supplier specialty code reported on the NPI’s Part B claims. For providers that have more than one Medicare specialty code reported on their claims, the Medicare specialty code associated with the largest number of services was utilized. Where a prescriber’s NPI did not have associated Part B claims, the taxonomy code associated with the NPI in NPPES was mapped to a Medicare specialty code using an external crosswalk published here: http://www.cms.gov/Medicare/Provider-Enrollment-and- Certification/MedicareProviderSupEnroll/Taxonomy.html. For any taxonomy codes that could not be mapped to a Medicare specialty code, the taxonomy classification description was used, and a description flag is included that describes the source of the specialty description.

description_flag – A flag variable that indicates the source of the specialty_description. “S” = Medicare Specialty Code description “T” = Taxonomy Code Classification description.

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drug_name – The name of the drug filled. This includes both brand names (for drugs that have patent protection) and generic names (for drugs that no longer have patent protection).

generic_name – A term referring to the chemical ingredient of a drug rather than the advertised brand name under which the drug is sold.

bene_count – The total number of unique Medicare Part D beneficiaries with at least one claim for the drug. Beneficiary counts fewer than 11 are not displayed.

total_claim_count – The number of Medicare Part D claims. This includes original prescriptions and refills. Claims counts fewer than 11 are not displayed.

total_day_supply – The aggregate number of days supply for which this drug was dispensed.

total_drug_cost – The aggregate total drug cost paid for all associated claims. This amount includes ingredient cost, dispensing fee, sales tax, and any applicable vaccine administration fees.

bene_count_ge65 – The total number of unique Medicare Part D beneficiaries with at least one claim for the drug where the beneficiary is 65 or older.. Beneficiary counts fewer than 11 are not displayed.

bene_count_ge65_redact_flag – A flag variable that indicates the reason the bene_count_ge65 variable was redacted.

“*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the “less than 65 year old” group (not explicitly displayed) contained a

small beneficiary count (<11) which could be mathematically determined from the “greater than or equal to 65 year old” beneficiary count and total beneficiary count.

ge65_redact_flag – A flag variable that indicates the reason the “greater than 65” variables were redacted.

“*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the “less than 65 year old” group (not explicitly displayed) contained a

small claim count (<11) which could be mathematically determined from the “greater than or equal to 65 year old” claim count and total claim count.

total_claim_count_ge65 – The number of Medicare Part D claims where the beneficiary is 65 or older. This includes original prescriptions and refills. Claims counts fewer than 11 are not displayed.

day_supply_ge65 – The aggregate number of days supply for which this drug was dispensed, where the beneficiary is 65 or older.

total_drug_cost_ge65 – The aggregate total drug cost paid for all associated claims where the beneficiary is 65 or older. This amount includes ingredient cost, dispensing fee, sales tax, and any applicable vaccine administration fees.

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brand_claim_count – Total claims of brand-name drugs, including refills. This is based on the Food and Drug Administration approval category of New Drug Application (NDA), NDA authorized generic, or Biologic License Application (BLA).

brand_claim_cost – Aggregate total drug cost paid for brand-name drugs. This amount includes ingredient cost, dispensing fee, sales tax, and any applicable vaccine administration fees. This is based on the Food and Drug Administration approval category of NDA, NDA authorized generic, or BLA.

brand_redact_flag – A flag variable that indicates the reason the “brand” variables were redacted. “*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the sum of claims from corresponding categories resulted in a small

claim count (<11) which could be mathematically determined using the claim count from this field and the total claim count.

generic_claim_count – Total claims of generic drugs, including refills. This is based on the Food and Drug Administration approval category of Abbreviated New Drug Application (ANDA).

generic_claim_cost – Aggregate cost paid for generic drugs. This amount includes ingredient cost, dispensing fee, sales tax, and any applicable vaccine administration fees. This is based on the Food and Drug Administration approval category of ANDA.

generic_redact_flag – A flag variable that indicates the reason the “generic” variables were redacted. “*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the sum of claims from corresponding categories resulted in a small

claim count (<11) which could be mathematically determined using the claim count from this field and the total claim count.

other_claim_count - Total claims of other drugs, including refills. This is based any other Food and Drug Administration approval categories not included in the brand or generic definitions above.

other_claim_cost – Aggregate cost paid for other drugs. This amount includes ingredient cost, dispensing fee and sales tax. This is based any other Food and Drug Administration approval categories not included in the brand or generic definitions above.

other_redact_flag – A flag variable that indicates the reason the “other” variables were redacted. “*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the sum of claims from corresponding categories resulted in a small

claim count (<11) which could be mathematically determined using the claim count from this field and the total claim count.

mapd_claim_count – The number of claims for beneficiaries covered by MAPD plans.

mapd_claim_cost – Aggregate cost paid for claims filled by beneficiaries in MAPD plans. This amount includes ingredient cost, dispensing fee, sales tax, and any applicable vaccine administration fees.

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mapd_redact_flag – A flag variable that indicates the reason the “MAPD” variables were redacted. “*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the “PDP” claim count contained a small claim count (<11) which could

be mathematically determined from the “MAPD” claim count and total claim count.

pdp_claim_count – The number of claims for beneficiaries covered by standalone PDPs.

pdp_claim_cost – Aggregate total drug cost paid for claims filled by beneficiaries in standalone PDPs. This amount includes ingredient cost, dispensing fee, sales tax, and any applicable vaccine administration fees.

pdp_redact_flag – A flag variable that indicates the reason the “PDP” variables were redacted. “*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the “MAPD” claim count contained a small claim count (<11) which

could be mathematically determined from the “PDP” claim count and total claim count.

lis_claim_count – Total number of claims from this prescriber, including refills, for beneficiaries with a Part D low-income subsidy.

lis_claim_cost – Aggregate total drug cost paid for claims for beneficiaries with a Part D low-income subsidy. This amount includes ingredient cost, dispensing fee and sales tax.

lis_redact_flag – A flag variable that indicates the reason the “LIS” variables were redacted. “*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the “non-LIS” claim count contained a small claim count (<11) which

could be mathematically determined from the “LIS” claim count and total claim count.

nonlis_claim_count – Total number of claims from this prescriber, including refills, for beneficiaries without a Part D low-income subsidy.

nonlis_claim_cost – Aggregate total drug cost paid for claims for beneficiaries without a Part D low- income subsidy. This amount includes ingredient cost, dispensing fee, sales tax, and any applicable vaccine administration fees.

nonlis_redact_flag – A flag variable that indicates the reason the “non-LIS” variables were redacted. “*” = Redacted due to small size (<11) of the data cell. “#” = Redacted because the “LIS” claim count contained a small claim count (<11) which could

be mathematically determined from the “non-LIS” claim count and total claim count.

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6. Data Limitations:

Although the Part D Prescriber PUF has a wealth of payment and utilization information about Medicare prescription drug events, the dataset also has a number of limitations that are worth noting.

First, the data in the Part D Prescriber PUF may not be representative of a prescriber’s entire prescribing pattern. The data contains information only from Medicare beneficiaries with Part D coverage, but clinicians typically treat many other patients who do not have that form of coverage. The Part D Prescriber PUF does not have any information on patients who are not covered by Medicare, such as those with coverage from other Federal programs (like the Federal Employees Health Benefits Program or Tricare), those with private health insurance (such as an individual policy or employer-sponsored coverage), or those who are uninsured.

The information presented in this file also does not indicate the quality of care provided by individual clinicians. The file only contains cost and utilization information, and for the reasons described in the preceding paragraph, the volume of prescriptions presented may not be fully inclusive of all prescriptions written by the provider. It should also be noted that since the data in this file are aggregated to the drug name level, the data do not account for varying strengths or dosage levels of the medications.

Additionally, the data in this file are limited to medications covered by the Part D program and those drugs excluded by the Part D program but covered by individual Part D prescription drug plans through supplemental benefits. The data does not include over-the-counter medications or any prescriptions obtained outside the Part D benefit. Since not all Part D plans have supplemental coverage for excluded products, utilization and cost statistics presented in the data likely underestimates the true use of these products in this population.

The total drug costs included in these data reflect the prescription drug costs incurred by Medicare Part D beneficiaries, including costs that are paid by Medicare, by beneficiaries, and by third-party payors. The Part D prescription drug program is administered by private Part D plan insurers. Medicare pays Part D plans a monthly, risk-adjusted capitation payment for each enrollee. Beneficiaries also pay a monthly premium. In addition, Medicare pays Part D plans additional subsidies to cover reduced cost- sharing for low-income beneficiaries and a portion of the costs for beneficiaries’ whose drug costs are very high. Following each benefit year, CMS shares risk with plans by reconciling the capitation and various subsidy payments to actual drug cost expenditures determined from Prescription Drug Event records, and any manufacturer rebates or other direct and indirect remunerations received by the plan. Therefore, because the drug expenditures derived from the Prescription Drug Event data comprise only a piece of the payment process, it is not possible to directly attribute total drug costs at the prescriber or drug level to payments from the Medicare trust fund. Furthermore, these total drug costs do not reflect any manufacture rebates.

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As noted earlier, the file does not include data for drugs that were filled 10 or fewer times, so users should be aware that summing data in NPI/drug detail file will underestimate the true Part D totals. These redactions may not be randomly distributed and can result in systematic differences (e.g., a prescriber who treats predominantly beneficiaries over 65 years old may have many redactions in the “ge65” variables due to cross-redaction). Redaction flag variables are included such that users may estimate the approximate magnitude of these redacted values.

There are some known issues in the attribution of PDEs to a specific NPI. Some prescribers’ claims may be listed under multiple NPIs, such as an organizational and individual NPI. In this case, users cannot determine a prescriber’s actual total because it is not possible to identify the individual’s portion when the claim is submitted under their organization. In addition, some of an individual’s prescriptions might be erroneously attributed to a different prescriber due to errors that can occur in the transcription of prescriber information at the point-of-sale.

Lastly, if users attempt to link data from these files to other public datasets, please be aware of the particular Medicare populations included and timeframes used in each file that will be merged, as well as the identifiers used to merge data. For example, efforts to link the Part D Prescriber data to the Physician and Other Supplier PUF data would need to account for the fact that some beneficiaries who have FFS Part B coverage (and are thus included in the Physician and Other Supplier PUF) do not have Part D drug coverage (and thus not represented in the Part D Prescriber PUF). At the same time, some beneficiaries that have Part D coverage (and are thus included in the Part D Prescriber PUF) do not have FFS Part B coverage (and thus not included in the Physician and Other Supplier PUF). Another example would be linking to data constructed from different or non-aligning time periods, such as publically available data on physician referral patterns, which is based on an 18-month period. Users attempting to merge data from the Part D Prescriber PUF to publicly available Open Payments data on financial relationships should be aware that NPIs are not available in the Open Payments data and thus merges must be conducted using text-string identification fields such as name and address.

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APPENDIX A – File Attributes

Table 1. NPI / Drug Name / Generic Name Detail File Layout # Variable Type Len Label 1 NPI Char 10 National Provider Identifier 2 NPPES_PROVIDER_LAST_ORG_NAME Char 70 Last Name/Organization Name 3 NPPES_PROVIDER_FIRST_NAME Char 20 First Name 4 NPPES_PROVIDER_CITY Char 40 Provider Business Practice Location Address

City Name 5 NPPES_PROVIDER_STATE Char 2 State Code 6 SPECIALTY_DESCRIPTION Char 91 Provider Specialty Type 7 DESCRIPTION_FLAG Char 1 Source of Provider Specialty 8 DRUG_NAME Char 30 Brand Name 9 GENERIC_NAME Char 30 USAN Generic Name - Short Version

10 BENE_COUNT Num 8 Number of Medicare Beneficiaries 11 TOTAL_CLAIM_COUNT Num 8 Number of Medicare Part D claims,including

refills. 12 TOTAL_DAY_SUPPLY Num 8 Number of days supply for all claims. 13 TOTAL_DRUG_COST Num 8 Aggregate cost paid for all claims. 14 BENE_COUNT_GE65 Num 8 Number of Medicare Beneficiaries, aged 65 or

older 15 BENE_COUNT_GE65_REDACT_FLAG Char 1 Flag detailing reason for redaction of

bene_count_ge65 field 16 TOTAL_CLAIM_COUNT_GE65 Num 8 Number of claims, including refills, where the

beneficiary was 65 or older. 17 GE65_REDACT_FLAG Char 1 Flag detailing reason for redaction of ge65

fields. 18 TOTAL_DAY_SUPPLY_GE65 Num 8 Number of days supply for all claims, where

the beneficiary is 65 or older. 19 TOTAL_DRUG_COST_GE65 Num 8 Aggregate cost paid for all claims, where the

beneficiary is 65 or older.

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Table 2. NPI Summary File Layout # Variable Type Len Label 1 npi Char 10 National Provider Identifier 2 nppes_provider_last_org_name Char 70 Last Name/Organization Name 3 nppes_provider_first_name Char 20 First Name 4 nppes_provider_mi Char 1 Middle Initial 5 nppes_credentials Char 20 Credentials 6 nppes_provider_gender Char 1 Gender 7 nppes_entity_code Char 1 Entity Code 8 nppes_provider_street1 Char 55 Street Address 1 9 nppes_provider_street2 Char 55 Street Address 2

10 nppes_provider_city Char 40 City 11 nppes_provider_zip Char 20 Zip Code 12 nppes_provider_state Char 2 State Code 13 nppes_provider_country Char 2 Country Code 14 specialty_description Char 91 Provider Specialty Type 15 description_flag Char 1 Source of Provider Specialty 16 bene_count Num 8 Number of Medicare Beneficiaries 17 total_claim_count Num 8 Number of Medicare Part D claims, including

refills. 18 total_drug_cost Num 8 Aggregate cost paid for all claims. 19 total_day_supply Num 8 Number of days supply for all claims. 20 bene_count_ge65 Num 8 Number of Medicare Beneficiaries, aged 65 or

older 21 bene_count_ge65_redact_flag Char 1 Flag detailing reason for redaction of

bene_count_ge65 field 22 total_claim_count_ge65 Num 8 Number of claims, including refills, where the

beneficiary was 65 or older. 23 ge65_redact_flag Char 1 Flag detailing reason for redaction of

other_claim_count field 24 total_drug_cost_ge65 Num 8 Aggregate cost paid for all claims, where the

beneficiary is 65 or older. 25 total_day_supply_ge65 Num 8 Number of days supply for all claims, where the

beneficiary is 65 or older. 26 brand_claim_count Num 8 Total claims of brand-name drugs, including

refills. 27 brand_redact_flag Char 1 Flag detailing reason for redaction of

brand_claim_count field 28 brand_drug_cost Num 8 Aggregate cost paid for brand-name drugs. 29 generic_claim_count Num 8 Total claims of generic drugs, including refills. 30 generic_redact_flag Char 1 Flag detailing reason for redaction of

generic_claim_count field

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31 generic_drug_cost Num 8 Aggregate cost paid for generic drugs. 32 other_claim_count Num 8 Total claims of other drugs, including refills. 33 other_redact_flag Char 1 Flag detailing reason for redaction

other_claim_count field of

34 other_drug_cost Num 8 Aggregate cost paid for other drugs. 35 mapd_claim_count Num 8 Number of claims for beneficiaries covered by

Medicare Advantage plans. 36 mapd_redact_flag Char 1 Flag detailing reason for redaction

mapd_claim_count field of

37 mapd_drug_cost Num 8 Aggregate cost paid for claims filled by beneficiaries in Medicare Advantage plans.

38 pdp_claim_count Num 8 Number of claims for beneficiaries covered by standalone prescription drug plans (not Medicare Advantage plans).

39 pdp_redact_flag Char 1 Flag detailing reason for redaction pdp_claim_count field

of

40 pdp_drug_cost Num 8 Aggregate cost paid for claims filled by beneficiaries in standalone prescription drug plans (not Medicare Advantage plans).

41 lis_claim_count Num 8 Number of claims for beneficiaries covered by the low-income subsidy.

42 lis_redact_flag Char 1 Flag detailing reason for redaction lis_claim_count field

of

43 lis_drug_cost Num 8 Aggregate cost paid for claims that were covered by the low-income subsidy.

44 nonlis_claim_count Num 8 Number of claims for beneficiaries not covered by the low-income subsidy.

45 nonlis_redact_flag Char 1 Flag detailing reason for redaction nonlis_claim_count field

of

46 nonlis_drug_cost Num 8 Aggregate cost paid for claims that were not covered by the low-income subsidy.

Table 3. National and State, Drug Name / Generic Name Summary File Layout # Variable Type Len Label 1 NPPES_PROVIDER_STATE Char 26 National Indicator or State Name of Provider 2 DRUG_NAME Char 30 Brand Name 3 GENERIC_NAME Char 30 USAN Generic Name - Short Version 4 BENE_COUNT Num 8 Beneficiary Count 5 PRESCRIBER_COUNT Num 8 Prescriber Count 6 TOTAL_CLAIM_COUNT Num 8 Total Claim Count 7 TOTAL_DRUG_COST Num 8 Total Drug Cost